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  # Plan_Q-RAG
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  ## Setup Rent GPU
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- Git Clone to all the required data
 
 
 
 
 
 
 
 
 
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  ```bash
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-
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  git clone https://github.com/griver/Q-RAG.git
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  cd Q-RAG
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- #Only need when you don't have your self-trained model
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  git clone https://huggingface.co/Q-RAG/qrag-ft-e5-on-hotpotqa
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  ```
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  Environment Setup
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  python -c "from rl.agents.pqn import PQNActor; print('✅ Q-RAG installed successfully')"
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  ```
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-
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  ```bash
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- cd ..
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-
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  python train_q_rag_logt.py \
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  envs=hotpotqa \
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  algo=pqn_e5_hotpotqa \
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  eval_interval=50 \ #original 100
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  envs_parallel=1 \
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  max_action_length=220
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-
 
 
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  python train_q_rag.py \
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  envs=hotpotqa \
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  algo=pqn_e5_hotpotqa \
 
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  # Plan_Q-RAG
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  ## Setup Rent GPU
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+ Git datasets for Q-RAG
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+ ```bash
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+ git clone https://huggingface.co/datasets/Q-RAG/Hotpotqa_and_Musique
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+ cd Hotpotqa_and_Musique
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+ unzip hotpotqa+musique.zip -d /workspace/datasets
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+ cd ..
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+ rm -rf Hotpotqa_and_Musique
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+ du -h
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+ ```
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+ Git repo of Q-RAG
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  ```bash
 
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  git clone https://github.com/griver/Q-RAG.git
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  cd Q-RAG
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+ #Only need when you don't have your self-trained hotpotqa model yet
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  git clone https://huggingface.co/Q-RAG/qrag-ft-e5-on-hotpotqa
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  ```
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  Environment Setup
 
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  python -c "from rl.agents.pqn import PQNActor; print('✅ Q-RAG installed successfully')"
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  ```
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+ Train: Log with Time
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  ```bash
 
 
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  python train_q_rag_logt.py \
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  envs=hotpotqa \
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  algo=pqn_e5_hotpotqa \
 
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  eval_interval=50 \ #original 100
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  envs_parallel=1 \
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  max_action_length=220
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+ ```
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+ Original Train
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+ ```bash
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  python train_q_rag.py \
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  envs=hotpotqa \
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  algo=pqn_e5_hotpotqa \